Data Science in Healthcare

There is a broad usage for data science in healthcare. Those who earn a degree in data science have an almost limitless array of job opportunities available to them within the medical field. What exactly is data science? What are the ways in which data science is used in the healthcare system today? What are the future implications of data science in the healthcare field? The paragraphs below will address these questions in more detail.

What is Data Science?

Data Science is a broad, interdisciplinary field that focuses on using modern technology to gather, study, analyze, and put to use various forms of data. The field of data science is broad and all-encompassing. It appeals to so many people because of the variety of skills and subjects that are utilized in order to make it successful. For example, data scientists are able to put their advanced mathematics, computer science, technology, statistics, and visualization skills to work all in one unique job setting. The constant diversity keeps the field challenging and interesting for those who choose to become experts in it.

How is Data Science Used in Healthcare?

Providing comprehensive health care for the millions of Americans walking the planet requires the use of many types of data. In fact, it’s estimated that at least 30% of the data that is generated today has to do with the healthcare field. This data is required in the clinical setting, financial avenues, and the business operations side of modern day healthcare.

The Value of Data and Data Analytics in Healthcare

We know that the gathering and use of this data is important in all three sectors of the healthcare field, but what data is gathered and how is it put to use? Raw data in and of itself is not highly regarded as being very useful. The true value of such data doesn’t become known until practical implications can be put to use with the information gathered from it. In short, data is used in the healthcare field to improve patient experiences, better understand compliance and adherence, assist patients in caring for themselves, and help avoid costly but unnecessary treatments.

The Use of Data Science in Precision Medicine

The future of the healthcare field lies in what is known as precision medicine. Precision medicine is the art of tailoring each patient’s medical treatment to him specifically. One avenue that is being pursued to accomplish making precision medicine more mainstream is the specialty of genetic testing. Genetic testing is used to some degree today, but proponents of it want to make it a mainstream part of modern healthcare. Genetic testing would involve the use of advanced technology, as well as scientific data analysis, to be able to capture, study, and make use of the genetic information tucked away inside every patient’s DNA code. Of course, our DNA code is unique to us and us alone. Every individual has a different DNA code, and no two people are exactly the same. The very premise behind genetic testing is that harnessing this unique set of information from each patient will allow for targeted medical treatments to be tailored to that person. By targeting the treatments to their specific set of genes, the theory is that these treatments will be more successful and cause fewer side effects.

Precision medicine would require the ability to comprehend and put to use a vast array of patient data. First of all, a large database consisting of all types of DNA profiles would need to be gathered. This would give medical professionals something to compare each future DNA profile against. Subsequently, data would continue to come in that would allow medical professionals to make important, targeted decisions about patient care, treatment options, and so on. Finally, data would be used to analyze how the treatment was succeeding and if any changes needed to be made to the patient’s care.

Data Science in Learning Healthcare Systems

A shift toward a learning based healthcare system is also being seen in many areas. In a learning based healthcare system, future medical practices are shaped by the successes and failures of the practices used in the past. These types of healthcare systems can be very successful in learning from past mistakes and replicating past successes. In effect, it goes along with the old reference to not reinventing the wheel, but rather learning from what was done in the past when caring for patients.

Learning based healthcare systems require constant use of data. For starters, data from past medical care and patient records must be carefully analyzed to determine what was successful at that time and what was not. This data would then be transformed into information that can be used to make effective current day implications for patient care.

The Vital Role of Data Scientists

Experts who gather, organize, study, and create modern day implications from all of this data being mentioned are referred to as data scientists. It is estimated that there are approximately 6,000 data scientists in the United States currently, but less than 200 of those are employed in the healthcare field. This number is remarkably low considering the current and future implications for the use of data science in healthcare. As the healthcare system continues to change and more focus is put on personalized medicine, we can expect to see a shift in the number of data scientists that are employed in the healthcare field.

Data science continues to be a growing field of interest for many college students and young professionals today. Due to the diversity of skills that are taught under the umbrella of data science, an individual with this degree is capable of working in a wide variety of sectors. Since nearly every successful company, organization, or business relies heavily on various types of data, it’s no surprise that data scientists remain in high demand. The use of data science in healthcare will continue to provide a multitude of interesting and challenging job opportunities over the coming years.

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